Low cost storage for rarely read data

ABSTRACT

Low cost storage for write once read rarely data is described. In an embodiment a storage device comprises a plurality of hard disk drives connected to a server via an interconnect fabric. The storage device comprises a cooling system which is only capable of cooling a first subset of the hard disk drives and a power supply system which is only capable of powering a second subset of the hard disk drives and in some examples, the interconnect fabric may be only capable of providing full bandwidth for a third subset of the hard disk drives. Each subset may comprise only a small fraction of hard disk drives. A control mechanism, which may be implemented in software, is provided which controls which hard disk drives are active at any time in order that the constraints set by the cooling and power supply systems and interconnect fabric are not violated.

RELATED APPLICATIONS

This application is a continuation of and claims priority to applicationSer. No. 14/516,154, filed on Oct. 16, 2014, and entitled “LOW COSTSTORAGE FOR RARELY READ DATA,” which is a continuation of and claimspriority to application Ser. No. 13/899,497, filed on May 21, 2013, andentitled “LOW COST STORAGE FOR RARELY READ DATA.” This applicationclaims the benefit of the above-identified applications, and thedisclosure of the above-identified applications are hereby incorporatedby reference in their entirety as if set forth herein in full.

BACKGROUND

There are large amounts of data which are written once to a data storagedevice and then subsequently only read rarely and examples includearchival storage of email and secondary geo-distributed replicas ofdata. On the rare occasions that this data is read, timely access isrequired and so use of magnetic tape based solutions (where robotic armsfetch tapes from a library and insert them into tape drive where theyare mechanically wound to the correct point), which are typically usedfor cold storage, is not appropriate because of the high access latency.Tapes can also be affected by environmental conditions (e.g. humidity)and so durability may be limited. Existing storage solutions whichprovide low latency access are based on physical hard disks and solidstate drives; however these have a high power consumption and are alsoexpensive to buy.

The embodiments described below are not limited to implementations whichsolve any or all of the disadvantages of known storage solutions.

SUMMARY

The following presents a simplified summary of the disclosure in orderto provide a basic understanding to the reader. This summary is not anextensive overview of the disclosure and it does not identifykey/critical elements or delineate the scope of the specification. Itssole purpose is to present a selection of concepts disclosed herein in asimplified form as a prelude to the more detailed description that ispresented later.

Low cost storage for write once read rarely data is described. In anembodiment a storage device comprises a plurality of hard disk drivesconnected to a server via an interconnect fabric. The storage devicecomprises a cooling system which is only capable of cooling a firstsubset of the hard disk drives and a power supply system which is onlycapable of powering a second subset of the hard disk drives and in someexamples, the interconnect fabric may be only capable of providing fullbandwidth for a third subset of the hard disk drives. Each subset maycomprise only a small fraction of hard disk drives. A control mechanism,which may be implemented in software, is provided which controls whichhard disk drives are active at any time in order that the constraintsset by the cooling and power supply systems and interconnect fabric arenot violated.

Many of the attendant features will be more readily appreciated as thesame becomes better understood by reference to the following detaileddescription considered in connection with the accompanying drawings.

DESCRIPTION OF THE DRAWINGS

The present description will be better understood from the followingdetailed description read in light of the accompanying drawings,wherein:

FIG. 1 is a schematic diagram of an example storage device;

FIG. 2 shows another schematic diagram of an example storage device;

FIG. 3 shows a schematic diagram of a first example interconnect fabric;

FIG. 4 shows a schematic diagram of a second example interconnectfabric;

FIG. 5 is a flow diagram of an example method of controlling accesses toa HDD;

FIG. 6 is a schematic diagram showing domains within a storage device;

FIG. 7 is a schematic diagram showing an example group construction thatachieves maximal disjointness;

FIG. 8 is a schematic diagram showing a representation of the HDDswithin a storage device from above;

FIG. 9 is a schematic diagram showing a representation of the HDDswithin a storage device from above in a two server scenario;

FIG. 10 shows flow diagrams of example methods of writing data to astorage device;

FIG. 11 shows a schematic diagram illustrating differences between twoof the methods shown in FIG. 10;

FIG. 12 shows a flow diagram of an example method of scheduling readoperations within a storage device;

FIG. 13 shows an example scheduling timeline for a storage device;

FIG. 14 is a flow diagram of another example method of reading data fromthe storage device; and

FIG. 15 illustrates an exemplary computing-based device in whichembodiments of the methods of controlling HDDs described herein may beimplemented.

Like reference numerals are used to designate like parts in theaccompanying drawings.

DETAILED DESCRIPTION

The detailed description provided below in connection with the appendeddrawings is intended as a description of the present examples and is notintended to represent the only forms in which the present example may beconstructed or utilized. The description sets forth the functions of theexample and the sequence of steps for constructing and operating theexample. However, the same or equivalent functions and sequences may beaccomplished by different examples.

FIG. 1 is a schematic diagram of an example storage device 100. Thestorage device 100 may be a rack-scale device (with a standard rack formfactor) or may have an alternative form factor. The storage devicecomprises a large number of hard disk drives (HDDs) 102 (e.g. over 1000HDDs) and a server 104. Each HDD 102 comprises a platter (or disc) whichis spun at high speeds when active (i.e. when data is being read orwritten). To reduce power consumption, the platters can be spun down(i.e. stopped); however, there is a latency associated with spinning upa platter and data cannot be read or written whilst a platter is spundown. For the purposes of the following description, this latency isassumed to be around 10 seconds, although it will be appreciated thatthe latency may be shorter or longer than this.

An interconnect fabric 106 is provided within the device whichinterconnects the HDDs 102 and the server 104. Power is provided by apower supply system 108, which although it is shown as a single block inFIG. 1 may be distributed throughout the storage device 100. Cooling(for the HDDs 102) is provided by a cooling system 110, which may forexample be a forced air cooling system using one or more fans to force(push or pull) air around the HDDs.

In the storage device 100, both the power supply system 108 and coolingsystem 110 are significantly underprovisioned such that the storagedevice 100 cannot support all the HDDs 102 being active (i.e. with theirplatters spinning) at one time and instead, the power supply system 108and cooling system 110 can only support a small fraction (e.g. 10% orless and in one example 8.3%) of the HDDs 102 being activesimultaneously. If all the HDDs 102 in the storage device 100 were tostart to spin their platters simultaneously, it would result in failureof the storage device 100 and consequently a mechanism is providedwithin the storage device 100 to control the number of HDDs 102 whichare active at any one time. This mechanism may be provided by softwarerunning on the server 104 (e.g. by a scheduler) and/or control logic 112within the storage device 100.

The underprovisioning of the power supply system 108 and the coolingsystem 110 within the storage device 100 (i.e. characteristics of thepower supply system and cooling system) set constraints on the number ofHDDs 102 that can be active at any time and these constraints may bereferred to as ‘hard constraints’ because if they are violated thestorage device 100 will (or is very likely to) fail. Dependent on thedesign of the storage device 100, there may be one or more other hardconstraints and/or one or more soft constraints. Examples of softconstraints may include a bandwidth constraint (e.g. a maximum bandwidthof an interface to the server 104 from an external network or bandwidthconstraint within the interconnect fabric 106) and a vibrationconstraint. Violation of a soft constraint does not cause failure (orvery likely failure) of the storage device 100 but instead will degradeperformance (e.g. exceeding a bandwidth constraint would slow access tothe device) and/or may cause longer term damage (e.g. exceeding avibration constraint is unlikely to cause failure of the storage devicein the short term but might, over a longer period of time, cause damagethat may ultimately lead to failure of the storage device 100). Theseconstraints (e.g. the power and cooling constraints and any additionalconstraints which may be used, such as a bandwidth constraint resultingfrom the interconnect fabric) are managed by the software running on theserver 104 and/or the control logic 112.

Although FIG. 1 shows the server 104 being located within the storagedevice 100, in some examples, the server 104 may be located outside thestorage device 100 and in some examples the server 104 may be locatedremotely from the storage device 100. Furthermore, although FIG. 1 showsa single server 104, it will be appreciated that the storage device 100may comprise more than one server (e.g. for redundancy purposes) andwhere there are multiple servers all the HDDs 102 may be connected to asingle server 104 (with the HDDs being switched to the second server inthe event of server failure) or the HDDs 102 may be split with a subsetbeing connected to one server and another (disjoint) subset beingconnected to another server (where these subsets may be fixed or may bedynamically changed over time). In some examples, there may be more thanone interconnect fabric 106 and more than one independent server 104,with the different interconnect fabrics 106 connecting the HDDs 102 tomultiple servers or to different servers. This provides resilienceagainst server and/or interconnect fabric failure.

The HDDs 102 are described herein as being active (i.e. having theirplatters spinning) or not being active (i.e. with their platters notspinning) which is also referred to herein as the HDD being in standbyas the electronics within the HDD are still powered. It will beappreciated that the HDDs 102 may have more than two states (active/notactive), such as being in transition from not active to active (i.e.where the platters are spinning up), being in transition from active tonot active (i.e. where the platters are spinning down), being fully off(i.e. no power to the electronics) and various other low power states.For the purposes of the following description the active state isconsidered to include both a state where the platters are spinning anddata is being read/written and a state where the platters are spinningand data is not being read/written (which may be referred to as an‘idle’ state) because both of these states consume a similar amount ofpower (e.g. 8 W). The spinning up state consumes a larger amount ofpower over a short period of time (e.g. 24 W for 10 seconds) and may beconsidered as part of the active state (e.g. for the purposes of poweraccounting) or separately. In an example implementation, the state ofeach HDD may be tracked as one of three states: standby (or not active),spinning up and active. It will be appreciated that in other examples,additional HDD states may also be considered (e.g. a fourth state ofspinning down may also be tracked where this takes a non-trivial amountof time to complete).

FIG. 2 shows another schematic diagram of an example storage device 100.This diagram shows an example 3D arrangement of the HDDs 102 in whicheach HDD 102 may be identified by its (x,y,z) coordinate. It will beappreciated that the HDDs 102 may not be located in a regular gridwithin an actual storage device 100; however, this representation, asshown in FIG. 2, provides a logical representation of the HDDs 102 forthe purposes of the following description.

The HDDs 102 within the storage device 100 may be arranged, as a resultof the device design, into disjoint (or non-overlapping) subsets whichare linked by a power constraint and in an example, the HDDs 102 may bearranged in trays 202 where HDDs 102 in a tray 202 have the same valueof x and z (and varying values of y) and one tray is shown as shadedcells in FIG. 2. The power constraint is set by the maximum amount ofpower that can be delivered to a tray. In an example, the powerconstraint may specify that only two HDDs may be active within a singletray and in some examples this constraint may be further qualified inthat only one of the two active HDDs may be in the spinning up state.Although FIG. 2 shows a storage device 100 with 35 trays, it will beappreciated that this is by way of example only and a storage device 100may comprise any number of trays. In an example, a storage device maycomprise 72 trays and each tray may comprise 16 HDDs.

The HDDs 102 within the storage device 100 may be further arranged intodisjoint subsets which are linked by a cooling constraint (e.g. wherethey are in the same air path within the cooling system 110). In anexample, the HDDs 102 may be arranged in columns 204, where HDDs in acolumn have the same value of x and y (and varying values of z) and onecolumn is shown as shaded cells in FIG. 2. In an example, the coolingsystem 110 may force air in at the front, up through a column and out atthe back of the storage device 100 (as indicated by arrow 206) and so itcan be seen that all the HDDs in column 204 are linked by a coolingconstraint as they are all located on the same cooling path (i.e. in thesame vertical airflow) through the device. In an example, the coolingconstraint may specify that only one HDD may be active within a singlecolumn. Although FIG. 2 shows a storage device 100 with 35 columns, itwill be appreciated that this is by way of example only and a storagedevice 100 may comprise any number of columns. In an example, a storagedevice may comprise 96 columns (with each column comprising 12 HDDs).

As can be seen from FIG. 2, columns and trays are not disjoint and thereis an overlap of one HDD between tray 202 and column 204. The twoconstraints are therefore not independent. Furthermore, the twoconstraints may set different upper limits on the total number of HDDswhich may be active in the storage device 100 at any one time and inwhich case, the lower of the two upper limits is used. For example, in asystem comprising 1152 HDDs arranged in trays of 16 HDDs and columns of12 HDDs, the power constraint sets a maximum number of HDDs active atany time of 144 (2 per tray, with 72 trays) whilst the coolingconstraint sets a maximum number of HDDs active at any time of 96 (1 percolumn, with 96 columns) and so the overall limit on the number ofactive HDDs at any time in the storage device is 96.

FIG. 3 shows a schematic diagram of a first example interconnect fabric300. This example shows an interconnect fabric for a storage devicecomprising two servers 302 where the second server is connected to (orconnectable to) all the HDDs 304, e.g. for redundancy in the case ofserver failure. It will be appreciated, however, that for a singleserver solution, the elements ringed by the dotted outline 306 may beomitted. This example interconnect fabric 300 uses PCI express (PCIe)and comprises a plurality of components 308-314 which are physicallydistributed within the storage device 100 to reduce the number of cables(to reduce the possibility of misconnections by humans) by replacingthem with PCB traces, to reduce the length of those PCB traces (as thePCI signal is degraded as it travels along the traces), to reduce thelength of any cables which are used (which reduces cost) and to extend(or optimize) the workable distance between a server 302 and a HDD 304.The workable distance is extended through distribution of componentswithin the storage device because each PCIe component reconditions thesignal.

As shown in FIG. 3, a server 302 is connected to a server switch 308 andthere is one server switch for each server. Each server switch 308 isconnected to a plurality of backplane switches 310 (denoted BS_(n)). Inthe example shown in FIG. 3 there are 6 backplane switches 310 connectedto a server switch 308 and in an example implementation, this connection(server switch 308 to each backplane switch 310) may be the onlyconnection which uses cables rather than PCB traces. A backplane switch310 connects to a plurality of tray switches 312 (denoted TS_(n)) and inthe example shown there are 12 tray switches connected to a backplaneswitch 310. It can be seen that where there are two servers 304, thereis no duplication at the tray switch level of the interconnect fabric,and each tray switch 312 connects to two backplane switches 310: onewhich is connected to the first server and one which is connected to thesecond server. As there are 6 backplane switches 310 (for each server302), there are a total of 72 tray switches 312 in the example shown inFIG. 3. Within a tray there are two SATA controllers 314 (denotedSC_(n)) and these connect the tray switch 312 to the individual HDDs304. As shown in FIG. 3, each SATA controller 314 connects to half ofthe HDDs 304 in the tray. As there are 72 tray switches in the exampleshown in FIG. 3, there are 144 SATA controllers connecting to a total of1152 HDDs, with each SATA controller being connected to 8 HDDs.

The interconnect fabric may provide a bandwidth constraint, as can beexplained with reference to FIG. 3; however, in some cases the bandwidthconstraint need not be considered explicitly when determining which HDDscan be active, for example where if the power and cooling constraintsare satisfied the bandwidth constraint is always also satisfied.

In the example shown in FIG. 3, each HDD 304 may have a 1 Gb/s link to aSATA controller 314, giving a total capacity at this level in theinterconnect fabric of 1152 Gb/s. At the next level up, each SATAcontroller 314 may have a 4 Gb/s link to a tray switch 312, giving atotal capacity at this level in the interconnect fabric of 576 Gb/s(half that of the previous level). Each tray switch 312 may then have a8 Gb/s link to a backplane switch 310, giving a total capacity at thislevel in the interconnect fabric of 576 Gb/s. Each backplane switch 310has a 16 Gb/s link to a server switch 308, giving a total capacity atthis level in the interconnect fabric of 192 Gb/s (one third of theprevious level) and each server switch 308 has a 32 Gb/s link to aserver 302. Alternatively, each tray switch 312 may have a 4 Gb/s linkto a backplane switch 310 (giving a total capacity at this level of only288 Gb/s or half that of the previous level) and each backplane switch310 may have a 8 Gb/s link to a server switch 308 (giving a totalcapacity at this level of only 96 Gb/s, which is one third of theprevious level). Both of these examples clearly demonstrate that if all96 HDDs which are permitted by the cooling and power constraints to beactive, are active, there is insufficient bandwidth within theinterconnect fabric 300 to read and/or write to them all. Consequentlyin this example, a bandwidth constraint (as a consequence of anunderprovisioned interconnect fabric) may also be considered whendetermining which HDDs are to be active at any one time. As describedabove, a bandwidth constraint is considered a soft constraint as itcauses congestion and latency and does not result in the failure of thestorage device.

FIG. 4 shows a schematic diagram of a second example interconnect fabric400 and in this example only a single server 402 is shown; however thefabric may be modified for use with two servers (e.g. by connecting eachof the top level multiplexers to both servers). This exampleinterconnect fabric 400 comprises a tree of SATA multiplexers 404 whichis connected to a small number of SATA ports provided on the server 402and uses the hotplug infrastructure within SATA. In this example, thetree is 6 layers deep, with two multiplexers 404 at the top level and486 multiplexers at the bottom level, which each connect to a pluralityof HDDs 406. It will be appreciated that for purposes of clarity not allthe multiplexers 404 or HDDs 406 are shown in FIG. 4. In this SATAimplementation, there is only one active route through the tree at anytime. Those HDDs which are not active are effectively hot unplugged whenthey transition from being active to being not active and they are nolonger visible (or in communication with) the server 402. This contrastswith the PCIe approach (interconnect fabric 300) shown in FIG. 3 inwhich there is direct connectivity to each HDD and this enablespre-emptive powering up of HDDs (i.e. powering up a set of HDDs whilereading from or writing to another set of HDDs), which is not possibleusing the interconnect fabric 400 shown in FIG. 4. Although FIG. 4 showsuse of SATA multiplexers 404, in a further example interconnect fabric,SATA multipliers may alternatively be used (however this would increasethe cost of the interconnect fabric and as SATA multipliers cannot bedaisy-chained, it would limit the number of HDD that could beconnected).

As described above, the power and cooling systems within the storagedevice 100 described herein (and shown in FIGS. 1 and 2) aresignificantly underprovisioned such that all the HDDs cannot be spun upsimultaneously (i.e. there is both insufficient power and insufficientcooling). In standard computing devices, however, the HDDs areautomatically spun up on start-up and processes may intermittently spinup HDDs for other purposes (e.g. when scanning files for viruses,indexing files to allow searching inside them, checking whether a diskis encrypted, checking disk failure prediction counters, checkingwhether a disk has been formatted in a legacy way, etc). To prevent thisin the storage device described herein, an access (or ‘no access’) flagmay be stored within the server for each HDD and then software runningon the server (e.g. the operating system) is modified such that when aHDD is marked ‘no access’ then all operations on that HDD fail. This isshown in the example flow diagram 500 in FIG. 5.

FIG. 5 is a flow diagram of an example method of controlling accesses toa MD. When an IO request for a HDD is issued, a check is performed tosee whether the ‘no access’ flag for the HDD is set (block 502) and ifthe flag is set (‘Yes’ in block 502), the IO request fails (block 504).However, if the flag is not set (‘No’ in block 502), the IO request ishandled normally (block 506). At start-up all non-boot HDDs may havetheir flags set (indicating ‘no access’) and HDDs may subsequently havetheir flags unset/set as they switch between non active and activestates. Depending on implementation, the flag may be set to either 1 or0 to indicate ‘no access’. In addition, the HDD driver may be modifiedto change how it discovers HDDs during the boot sequence. Such amodified driver is arranged to spin-up, probe, identify and thenspindown each HDD in sequence. Existing drivers may perform staggeredspin up of HDDs, but do not spin down one HDD before spinning up thenext HDD.

As described above, the power and cooling (and potentially other)constraints limit the number of HDDs that can be active within thestorage device at any time and software running on the server and/orcontrol logic is used to control which HDDs are active (and setcorresponding access flags, where these are used). Referring back to theexample storage device shown in FIG. 2, the HDDs within a storage devicemay be represented as a regular grid of cells, with each cellcorresponding to a HDD 102 and each HDD being referenced by an (x,y,z)coordinate. As described above, the cooling constraint operates within acolumn 204 and this may be referred to as a ‘cooling domain’, with twoHDDs that have the same x and y coordinates sharing a cooling domain.Similarly, the power constraint operates horizontally within a tray andthis may be referred to as a ‘power domain’, with two HDDs that have thesame x and z coordinates sharing a power domain. The term ‘slice’ may beused to refer to the smallest part of the storage device for which powerand cooling domains are self-contained and HDDs that have the same xcoordinates are in the same slice and HDDs from two different slicescannot share power or cooling domains. FIG. 6 is another schematicdiagram showing domains within a storage device 600 and in this example,a slice 602 is shown separate from the rest of the storage device. FIG.6 also shows the power domain 604 and the cooling domain 606 of a HDD608 in the slice 602.

In various examples, the HDDs within the storage device may be dividedlogically into non-overlapping groups with each group comprising aplurality of HDDs which can all be active simultaneously withoutviolating the power and cooling constraints. In such examples, each HDDis a member of a single group and it will be appreciated that a groupdoes not comprise all the HDDs that can be active simultaneously (e.g.multiple groups may be active simultaneously). In an exampleimplementation, the HDDs may be partitioned into logical groups suchthat each group has the same number of HDDs (e.g. 16 HDDs) and HDDs ofone group can be cooled and powered together (i.e. they do not violatethe power or cooling constraints). In some examples, there may be alsobe a bandwidth (soft) constraint that HDDs of one group have nobandwidth conflicts within the interconnect fabric unless they saturatethe root of the tree (e.g. the PCIe tree shown in FIG. 3).

Some of the groups will be mutually exclusive because domains (coolingand/or power) of their HDDs overlap and these groups may be described ascolliding. Groups that are not colliding may be described as beingdisjoint and by grouping HDDs to maximize the disjointness of the HDDs(i.e. to maximize the probability that any HDD within one group is notin the same cooling or power domain as a HDD in another group), theprobability that two groups selected at random can be activesimultaneously is increased and the throughput of the storage device isincreased. An example layout which maximizes group disjointness is onewhere two groups are arranged to be either disjoint or to collide fully(i.e. each HDD of the first group is in the cooling and power domain ofHDDs in the second group).

FIG. 7 shows an example group construction (for 16 HDD per group) thatachieves maximal disjointness. FIG. 7 shows two groups 702, 704 and HDDswithin each group are placed along a diagonal to avoid in-groupcollisions. It can clearly be seen that each HDD in the first group 702is in both a power domain and a cooling domain of HDDs in the secondgroup 704. Taking an example HDD 706 in the first group 702, it is inthe power domain of one HDD 708 in the second group 704 and in thecooling domain of a second HDD 710 in the second group. As each groupcontains more HDDs than there are power domains (12 power domainscompared to 16 HDDs) in a single slice (and where in this example thereare fewer power domains than cooling domains, so this is the limitingfactor), each group comprises HDDs from two slices 712, 714 and thisexample the two slices are adjacent to each other within the storagedevice. Using the example arrangement shown in FIG. 7, it is possible tobuild 72 well-formed groups of 16 HDDs. Each group is fully collidingwith 11 groups in the same slice and can be concurrently spun up withany of the remaining 60 groups.

If the group placement strategy described above is used, it is a simpleoperation to identify joint-groups (i.e. groups that collide): twogroups share power and cooling domains if (and only if) they are locatedin the same slices. A line of a group may be defined as the equivalenceclass that contains all the groups that are joint with the group andthis is shown in FIG. 8. FIG. 8 is a schematic diagram showing arepresentation of the HDDs within a storage device from above. Each cell802 represents a cooling domain and each row 804 represents a slice.Each line is shown by way of shading and is composed of 12 groups of 16HDDs that completely overlap power and cooling domains. Each line hasthe properties that: groups from the same line should be scheduledsequentially and groups from any two lines can spin up and be active(e.g. perform IO) concurrently. Referring to the specific example shownin FIG. 8, each group of any line can spin up concurrently with anygroup of the other lines and any two of the 6 lines can be activeconcurrently.

In a storage device which comprises two servers which are active at thesame time (rather than switching between the servers on server failure),the groups may be assigned to servers in order to prevent inter-serverscheduling conflicts and as shown in FIG. 9 a mapping between slices andservers may be used. Using a mapping from slice to server is beneficialas a slice is self-contained in terms of cooling/power domains and asshown in FIG. 9, lines may be re-arranged so that any slice will belongto exactly one server. Comparing FIGS. 8 and 9 it can be seen that inthe multi-server scenario of FIG. 9, line 1 wraps from the first sliceto the third slice (instead of the sixth slice) in order that the firstthree slices can be mapped to the first server. Similarly, line 4 wrapsfrom the fourth slice to the sixth slice (instead of the third slice).

Although the examples described above show groups of 16 HDDs, in otherexamples different sizes of groups may be used (i.e. different numbersof HDDs). In some examples, the size of a group may be selected suchthat it divides evenly into (i.e. is a factor of) the maximum number ofconcurrently active disks (e.g. is a factor of 96 in many of theexamples described herein), i.e. such that an integer number of groupscan be active concurrently, as this improves efficiency. Spinning uppart of a group (e.g. half a group) is less efficient and more complexto control than spinning up only complete groups as any IOs will requirethe entire group to be active. Smaller group sizes (i.e. groupscomprising a smaller number of HDDs) improves scheduling performancebecause the number of groups is higher and the scheduler has morefreedom to choose which group to schedule next (see discussion ofscheduling below with reference to FIGS. 12 and 13). However, smallgroups offer less throughput per group (and therefore per operation) andincur a larger overhead where erasure coding and striping (as describedbelow) is used. For a one server solution (i.e. where only one server isoperating at any time) with the architecture described above (72 trays,each comprising 16 HDDs, giving a total of 1152 HDDs), reasonable groupsizes may include 16 HDDs (6 active groups at any time), 24 HDDs (4active groups at any time), 32 HDDs (3 active groups) or 48 HDDs (2active groups). For a two server scenario (and still with anarchitecture comprising 72 trays of 16 HDDs), there may be 16 HDDs in agroup (3 spinning groups per server) or 24 HDDs (2 groups per server).It will be appreciated that for other architectures, different groupsizes may be used.

FIG. 10 shows flow diagrams of example methods of writing data to astorage device as described herein. The first example method 1000 usesthe concept of groups of HDDs as described above. As shown in method1000, a burst of data which is to be written to the HDDs is divided(prior to being presented to the server) into portions, which may bereferred to as ‘extents’, and these extents are received by the server(block 1002). Extents may be of a variable size (e.g. within a rangedefined by a minimum and maximum size) and each extent may, for example,be 1 GB (or larger) in size. Error correction is then added to eachextent (block 1004) and any suitable error correction technique may beused. This error correction may be added by the server or an externalparty. In an example, erasure coding may be used and in other examples,other methods, such as parity checks, may be used. Each extent is thenwritten to the HDDs from a single group (block 1006). This means thatwhen reading the extent, it is guaranteed that the entire extent can beread simultaneously and it will not be necessary to switch betweengroups (i.e. by transitioning a first group to being non active andspinning up the platters of the HDDs in a second group) in the middle ofreading an extent (which would add considerable latency).

FIG. 10 also shows a more detailed example method 1010 of writing datato a storage device described herein. In this method 1010, a singleextent is divided into fixed size stripes (block 1012) and each stripeis then split into a fixed number, k, of blocks (block 1014), where k isan integer. Depending on the error correction technique used, j blocksmay be added to encode redundancy information for each stripe (block1016), where j is an integer, such that each stripe now comprises (k+j)blocks. A block from each stripe is then written to a different one of(k+j) HDDs from the same group (block 1018). In this way, all blocksacross all stripes are written to the same (k+j) HDDs and as in thefirst method 1000, each extent (or portion) is written to HDDs from asingle group.

The second method 1010 may alternatively be described in terms of‘stripe stacks’. Having added the j redundancy blocks (in block 1016),blocks with the same offset in each stripe are assembled into stripestacks (block 1020). For example, if there are m stripes and a firststripe comprises (k+j) blocks denoted B_(1,1), B_(1,2), . . . ,B_(1,(k+j)) and the m^(th) stripe comprises (k+j) blocks denotedB_(m,1), B_(m,2), . . . , B_(m(k+j)), then one stripe stack comprises mblocks B_(1,1), B_(2,1), . . . , B_(m,1) and another stripe stackcomprises blocks B_(1,2), B_(2,2), . . . , B_(m,2) etc. As can be seen,each stripe stack comprises m blocks, with the x^(th) stripe stackcomprising the x^(th) block from each of the m stripes. Each stripestack is then written to a different HDD within a group (block 1022).

FIG. 10 also shows a third example method 1030 of writing data to astorage device described herein. While the second example method 1010may be referred to as ‘striping’, this third example method 1030 may bereferred to as ‘segmenting’ and this method 1030 does not use theconcept of groups (unlike methods 1000 and 1010). In this example method1030, the extent is divided into n segments (block 1032) and predundancy segments are added (block 1034). Each segment within theextent is then stored on a different HDD (block 1036), i.e. one segmenton each of (n+p) HDDs. In this example the (n+p) HDDs do not necessarilybelong to the same group, but instead the size of the segment isselected such that reading it from a HDD would take at least 10 seconds(i.e. at least the time taken to spin up a HDD) and the HDD storingsegment i+1 should be spinnable concurrently with the HDD storingsegment i. This means that when reading an extent which has been writtenusing method 1030, the HDD storing segment 1 from an extent is initiallyactive and in parallel the HDD storing segment 2 from the same extent isspinning up. When segment 2 is being read, the HDD storing segment 1 isspun down (i.e. the platter is no longer being driven) and the HDDstoring segment 3 is spinning up, etc.

FIG. 11 shows a schematic diagram of striping (as shown in method 1010)compared to segmenting (as shown in method 1030). This diagram shows thesituation for k=1, j=1, n=1 and p=1. Segmenting is more flexible for thescheduler (which controls writes to the HDDs) than striping because theconstraint is that HDDs storing two consecutive segments must bespinnable together (rather than all the HDDs having to belong to onegroup). However, the throughput of segmenting is limited to thebandwidth of one HDD, scheduling may be more complex as there arepotentially many conflicting parallel operations required to saturatethe storage device bandwidth and it requires DRAM proportional to themaximum extent size. Striping, in contrast, provides a high throughputand scheduling is less complex because it is quasi-oblivious to thepower and cooling constraints (as these are taken care of by the groupdefinitions); however, there is less flexibility for the scheduler asall the HDDs storing the extent must be from one group (and hencespinnable together).

When writing data to groups of HDDs in the first two example methods1000, 1010 (e.g. as in blocks 1006 and 1018) the data (i.e. the extents)may be fairly spread across all groups (“even fill”) or one group may befilled with data before filling the next one (“sequential fill”). In oneexample implementation, even fill of groups is used. Even fill resultsin equal loading of HDDs (which makes maintenance easier) and there isless data to rebuild in the case of HDD failure (as a HDD is unlikely tobe completely filled with data); however there may be a lower throughput(than for sequential fill) when the storage device is lightly loaded(i.e. each group is storing a small amount of data) because there arefewer IO per active MD. In contrast, sequential fill provides more IOsper HDD in a lightly loaded storage device (as the data will beconcentrated in a small number of groups), but some HDDs may be inactivefor very long periods and this may impact HDD reliability.

As well as controlling writes to the HDDs, a scheduler within the servercontrols read operations on the HDDs. FIG. 12 shows a flow diagram of anexample method 1200 of scheduling read operations within a storagedevice. This method uses the concept of groups and therefore may be usedin combination with one of methods 1000 and 1010 for writing data. Onreceipt of a burst of read operations (block 1202), the scheduler ordersoperations into sets which operate on the same group of HDDs (block1204) and then schedules sets of operations in an order which maximizesthroughput (block 1206), e.g. by minimizing switching between groups. Insome examples, operations may be flagged with a priority level, in whichcase the sets of operations may be scheduled on the basis of boththroughput and priority (in block 1206).

In order to maximize throughput, sets of operations may be ordered (inblock 1206) to allow groups to be spun up, while attempting to maintainthe interconnect fabric's throughput. For example, if it takes 10seconds to spin up a HDD, each set of operations may be arranged toprovide at least 10 seconds of IO operations in order that another groupmay be spun up whilst a set of operations is being performed. Forexample, between t=t₁ and t=t₁+10, operations are performed on group Aand HDDs in group B are spinning up, then between t=t₁+10 and t=t₁+20,operations are performed on group B and HDDs in group C are spinning up,etc. Sets of operations which operate on disjoint groups can bescheduled in parallel, as long as there is sufficient bandwidth in theinterconnect fabric (i.e. as long as a bandwidth constraint is notviolated). For example, between t=t₁ and t=t₁+10, operations areperformed on groups A and D and HDDs in groups B and E are spinning up,then between t=t₁+10 and t=t₁+20, operations are performed on groups Band E and HDDs in groups C and F are spinning up, etc, where groups Aand D, B and E and C and F are disjoint. As the bandwidth constraint isnot a hard constraint, in some examples, underprovisioned bandwidth maybe shared between groups such that each group experiences a bandwidthrestriction. For example if there are two operations which each use 18GB/s of bandwidth and the total available bandwidth is only 32 Gb/s, thetwo operations may be served concurrently at 16 Gb/s, rather thanserving just a single operation at the full bandwidth of 18 Gb/s.

Referring back to FIGS. 8 and 9, if the groups of HDDs are arranged inlines, the scheduler may be aware of these lines and which lines canexecute concurrent IOs (as described above). Consequently, the scheduler(in block 1206), may group sets of operations based on this lineknowledge and the following criterion may also be used: IOs from twogroups of the same line are be separated by at least 10 seconds worth ofIO from groups belonging to other lines. This enables the second groupfrom the same line to be spun up during the separation period. It willbe appreciated that although the spin up time is assumed to be 10seconds, the same principle may be applied if the spin up time is alonger or shorter period of time. In scheduling groups (in block 1206),the scheduler may, for example, use an inexpensive greedy algorithm todetermine which group to schedule next in order to minimize idle time.

The scheduling of operations (in block 1206) may apply within a burst ofread operations (as received in block 1202) or alternatively a window(which may be defined in terms of time or number of operations) may beused to define how may operations in a queue of read operations may beconsidered for rescheduling at the same time (e.g. a window of 100 or1000 operations). Where such a window is used, the method of FIG. 12 maybe applied even where read operations are not received in bursts (i.e.block 1202 omitted) and in such examples, the reordering andrescheduling (in blocks 1204 and 1206) may be applied on a window ofreceived read operations which are held in a queue.

Where a queue of read operations is reordered (in block 1206) any delay(e.g. over a threshold delay) may be fed back to the requester (i.e. theentity sending the read request).

Although the description of FIG. 12 above relates to read operations, insome examples, the same method may be applied to delete operations.

FIG. 13 shows an example scheduling timeline 1300 for a storage devicecomprising groups of 16 HDDs and the PCIe interconnect fabric shown inFIG. 3. With groups of 16 HDDs, 2 groups are able to fully use the PCIebandwidth, therefore at any given moment, 2 groups are doing IO. In thescheduling timeline 1300, at each step the scheduler selects groups tospin up that have enough IO to overlap the transition between two joint(i.e. colliding) groups, which as described may take about 10 seconds.

Many of the methods described above rely on the HDDs within the storagedevice being logically arranged into fixed groups, where HDDs in a groupcan be active at the same time. In some examples, however, there may beno fixed groups and instead the set of HDDs which are active at any timemay be determined by the scheduler within the server (or another elementwithin the server) based on power constraints, cooling constraints andin some examples some other constraints (e.g. a vibration constraint).Such examples use the concept of domains (as described above withreference to FIG. 2), where a domain is a set of HDDs, and a set ofconstraints that hold on the domain. For example, a cooling domain has aconstraint expressed in Watts, as does a power domain. A single HDD is amember of multiple domains.

Each of the per-domain constraints is mapped to a set of HDD-orientatedconstraints, i.e. a set of HDD states that can be tolerated by thedomain. In the examples above, each HDD is described as being in one oftwo, or in some examples three, states: not active (i.e. platters notspinning, but electronics powered), spinning up (i.e. platters inprocess of transitioning from not spinning to spinning at correct speed)and active (i.e. platters spinning). As described above, in someexamples, there may be more states considered, such as differentiating,for a HDD with the platters spinning between when data is and is notbeing read/written. For the power domain, the power draw of each statebeing considered within the system is known and similarly, for thecooling domain, the cooling load of each state is known. For example, aHDD draws 0.7 W when in standby (or non active state, i.e. electronicspowered, platters not spinning), 8 W when active (platters spinning) and24 W for 10 seconds when the platters are spinning up. A budget cantherefore be expressed for each domain as the set of possible statesthat can be supported by the domain. Referring back to a previousexample architecture, the power budget for a domain may be two activeHDDs per power domain or one active HDD and one HDD spinning up and thecooling budget may be one active or spinning up HDD per cooling domain.The budget may, for example, be expressed as a state table or finitestate machine.

FIG. 14 is a flow diagram of an example method of reading data from thestorage device where domains are used (as described above). In thisexample, when a read request for a file is received (block 1402), thescheduler within the server determines the set of HDDs that need to bespinning in order to read the file (block 1404). This set is likely tobe different from the currently spinning HDDs and so the scheduler thendetermines a migration sequence from the current set of spinning HDDs tothe required set of spinning HDDs (which may be referred to as the‘target configuration’), where the migration sequence does not passthrough any intermediate set of HDDs which violates any of the domainconstraints (block 1406). This is therefore an optimization problem tobe solved which selects the set of hardware configuration states thatneed to be passed through in order to get to a configuration where thefile can be read. Once the migration sequence is determined, it can beimplemented (block 1408) and the file read (block 1410).

In implementing the method of FIG. 14, a burst of read operations may beconsidered (e.g. as described above with reference to FIG. 12) and inwhich case the migration sequence may be determined to optimize thethroughput for the burst rather than a single request. In such anexample, the time taken to spin up platters (e.g. 10 seconds) may betaken into consideration in the same way as described previously and IOrequests may be grouped into operations on common sets of HDDs whichlast at least 10 seconds.

The scheduling shown in FIGS. 12 and 13 and described above an operation(e.g. accessing a set of stripe stacks) is associated with a set of HDDswhich need to be accessed. Where two operations do not conflict (i.e.there is no overlap between sets of HDDs) they can execute in parallel.If, however, all the HDDs are in conflict, operations are processedsequentially. If, however, only a fraction of the HDDs conflict, twodifferent scheduling mechanisms may be used and in the methods describedabove, a mechanism which may be referred to as ‘non-preemptivescheduling’ may be used.

With ‘non-preemptive scheduling’, 100% of one of the two conflictingoperations is processed and the second one is stalled (even if the twooperations have as few as one HDD in conflict). The second operation isprocessed (in its entirety) when the conflict has been resolved (e.g.when the first operation has been completed). In contrast for‘preemptive scheduling’, 100% of one of the two conflicting operationsis processed and the non-conflicting n % of the other operation isprocessed in parallel, with the remaining (100−n)% being finished later.

In preemptive scheduling, which may be used with the method shown inFIG. 14 the scheduling is performed at HDD granularity: the schedulerdecides which HDD to spin up next regardless of which operations arecurrently processed. The scheduler is domain-aware and schedules HDDsthat are not in conflict. For non-preemptive scheduling, however, thescheduler either spins up all the HDDs required for an operation ordelays the operation if this is not possible. The scheduler isdomain-oblivious and focuses on operation-conflict avoidance.

Preemptive scheduling potentially has increased scheduling flexibilitybut this results in increased scheduling complexity. Preemptivescheduling also potentially has higher throughput but higher latency peroperation as several spin up times may be required per operation.Preemptive scheduling also uses large in-memory buffers at the server tostore pending operations, which increase the cost of the storage deviceand decreases its reliability. Non-preemptive scheduling, in contrast,provides guarantees in terms of throughput per operation and has lowmemory requirements.

In addition to considering power and cooling domains in any of themethods described above (e.g. in any of the methods shown in FIGS. 10,12 and 14), other constraints (e.g. soft constraints) and other domainsmay also be taken into consideration. Soft constraints are those whichif violated yield sub-optimal performance but will not result inhardware failure (as is the case for hard constraints such as the powerand cooling constraints). The soft constraints may be expressed based ondomains, for example failure and physical locality. The failure domaincaptures sets of HDDs and the likelihood that they will concurrentlyfail. The physical locality captures the locality properties of theinterconnect fabric and may be expressed in terms of functions thatgiven two HDDs returns a value V between 0 and 1. The value, V,represents the interference between the two HDDs (1=no interference,while a value less than 1 represents the strength of the relationship).Given a nominal bandwidth A per HDD, the expected maximum throughput ofboth HDDs are reading/writing concurrently is V×A.

FIG. 15 illustrates various components of an exemplary computing-baseddevice 1500 which may be implemented as any form of a computing and/orelectronic device, and which may operate as a server within the storagedevice described herein.

Computing-based device 1500 comprises one or more processors 1502 whichmay be microprocessors, controllers or any other suitable type ofprocessors for processing computer executable instructions to controlthe operation of the device in order to operate as a server and controlread/write operations to the HDDs in the storage device. In someexamples, for example where a system on a chip architecture is used, theprocessors 1502 may include one or more fixed function blocks (alsoreferred to as accelerators) which implement a part of the method ofcontrolling the HDDs in hardware (rather than software or firmware).Alternatively, or in addition, the functionality described herein can beperformed, at least in part, by one or more hardware logic components.For example, and without limitation, illustrative types of hardwarelogic components that can be used include Field-programmable Gate Arrays(FPGAs), Program-specific Integrated Circuits (ASICs), Program-specificStandard Products (ASSPs), System-on-a-chip systems (SOCs), ComplexProgrammable Logic Devices (CPLDs).

Platform software comprising an operating system 1504 or any othersuitable platform software may be provided at the computing-based deviceto enable application software 1506 and scheduler 1508 to be executed onthe device. The computer executable instructions may be provided usingany computer-readable media that is accessible by computing based device1500. Computer-readable media may include, for example, computer storagemedia such as memory 1510 and communications media. Computer storagemedia, such as memory 1510, includes volatile and non-volatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM,flash memory or other memory technology, CD-ROM, digital versatile disks(DVD) or other optical storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othernon-transmission medium that can be used to store information for accessby a computing device. In contrast, communication media may embodycomputer readable instructions, data structures, program modules, orother data in a modulated data signal, such as a carrier wave, or othertransport mechanism. As defined herein, computer storage media does notinclude communication media. Therefore, a computer storage medium shouldnot be interpreted to be a propagating signal per se. Propagated signalsmay be present in a computer storage media, but propagated signals perse are not examples of computer storage media. Although the computerstorage media (memory 1510) is shown within the computing-based device1500 it will be appreciated that the storage may be distributed orlocated remotely and accessed via a network or other communication link(e.g. using communication interface 1512).

In some examples the computing-based device 1500 may be managed remotelyand in which case, the communication interface 1512 may be arranged toreceive management instructions from a remote management entity and toprovide status/update information to the remote management entity.

The memory 1510 may further comprise a data store 1514 which may be usedto store access flags for each HDD in the storage device (e.g. asdescribed above with reference to FIG. 5).

The computing-based device 1500 also comprises a server switch 1516arranged to output signals to each of the backplane switches via aninterconnect fabric (e.g. as described above with reference to FIG. 3 or4). These signals control the state of the HDDs and also are used whenwriting to or reading from an HDD. Alternatively, where the SATA basedinterconnect fabric 400 is used, the server switch 1516 is replaced byan HDD controller, which provides a plurality of SATA ports eachconnecting to a SATA multiplexer 404 at the top level of the tree.

The computing-based device 1500 may also comprise an input/outputcontroller arranged to output display information to a display devicewhich may be separate from or integral to the computing-based device.The display information may provide a graphical user interface. Theinput/output controller may also be arranged to receive and processinput from one or more devices, such as a user input device (e.g. amouse, keyboard, camera, microphone or other sensor). In some examplesthe user input device may detect voice input, user gestures or otheruser actions and may provide a natural user interface (NUI). In anembodiment the display device may also act as the user input device ifit is a touch sensitive display device. The input/output controller mayalso output data to devices other than the display device.

Any of the input/output controller, display device and the user inputdevice (where provided) may comprise NUI technology which enables a userto interact with the computing-based device in a natural manner, freefrom artificial constraints imposed by input devices such as mice,keyboards, remote controls and the like. Examples of NUI technology thatmay be provided include but are not limited to those relying on voiceand/or speech recognition, touch and/or stylus recognition (touchsensitive displays), gesture recognition both on screen and adjacent tothe screen, air gestures, head and eye tracking, voice and speech,vision, touch, gestures, and machine intelligence. Other examples of NUItechnology that may be used include intention and goal understandingsystems, motion gesture detection systems using depth cameras (such asstereoscopic camera systems, infrared camera systems, RGB camera systemsand combinations of these), motion gesture detection usingaccelerometers/gyroscopes, facial recognition, 3D displays, head, eyeand gaze tracking, immersive augmented reality and virtual realitysystems and technologies for sensing brain activity using electric fieldsensing electrodes (EEG and related methods).

In the above examples, the constraints are set by the design of thestorage device and hence may be considered fixed. Where groups are used,these are determined by the constraints and may therefore also beconsidered fixed. In the event of hardware failure, however, the servermay be arranged to modify the constraints (and hence groups, where theyare used) in order that the storage device can continue to function,even if performance may be degraded. For example, a storage device maycomprise 6 power supply units, each powering a number of trays (e.g.powering 12 trays) and where a power supply unit fails, another powersupply unit within the storage device may be shared between a largernumber of trays (e.g. between 24 trays) and the constraints and/orgroups may be dynamically adapted to respond to this. Theconstraints/groups may also be modified (e.g. dynamically adapted) inevent of replacing any of the hardware (e.g. the HDDs) with moreefficient hardware (e.g. the power and/or cooling constraints associatedwith a more efficient HDD may be different, enabling larger or differentsize groups).

In the event of hardware failure, there may be one or more recoverymechanisms operational within the storage device in addition to, orinstead of, adapting the constraints and/or groups. Examples include:maintaining spare capacity within a group to handle HDD failure (e.g.each group comprises one or two more HDDs than are used for eachoperation), maintaining a spare group of HDDs for redundancy purposes(e.g. which can be switched in to replace a group experiencing HDDfailure), and spreading load across other groups.

Although the present examples are described and illustrated herein asbeing implemented in a storage device comprising one or two servers, thesystem described is provided as an example and not a limitation. Asthose skilled in the art will appreciate, the present examples aresuitable for application in a variety of different types of storagesystems, for example, multiple storage devices may be co-located (e.g.in a data center) and there may be some sharing of resources (e.g. powersupply units) in the event of failure. Furthermore, although two exampleinterconnect fabrics 300, 400 are described above, alternative designsof interconnect fabric maybe used.

As described above, in some examples the server 104 may be locatedremotely from the rest of the storage device 100. In such examples,control logic 112 may be provided within the storage device 100 andarranged to provide control signals to the HDDs 102 via the interconnectfabric 106 in response to signals received from the remote server.

The storage device described above is intended for minimal read/writeaccess to the HDDs and therefore is configured to keep the majority ofHDDs in a sleeping (i.e. not active) state where they consume minimalpower (the electronics are powered but the platters are not spinning).The HDDs are only brought out of this state to initially write the data,check the data for integrity or to retrieve the data; however, since thedata type for which the storage device is designed is archival,retrieval operations are expected to be minimal. Consequently, thestorage device may be designed to use minimal power and associatedcooling. For the example configuration comprising 1152 HDDs (asdescribed above), the storage device may be designed to use 2.4 kW orless than 25% of existing storage devices (with similar storagecapacity). This requires less power distribution (within the storagedevice), smaller fans and enables a greater packing density of HDDs duea lower volume of cooling (e.g. forced air) going through the storagedevice. As described above, the storage devices described herein areunderprovisioned such that they are not capable of providing sufficientpower and/or cooling for all of the HDDs in the device (i.e. theyphysically cannot spin up all the HDDs concurrently). In an example, thestorage device may provide sufficient power and cooling for only around10% or less (e.g. 8.3%) of the HDDs to be active at any one time. Thisunderprovisioning reduces the power consumption and hence operatingexpense of the device and the reduced bandwidth of the device may alsocontribute to a further reduction in he operating costs. The higherpacking density of HDDs which is enabled and the reduction in the powerand cooling infrastructure contributes to lower initial costs of thestorage device to buy (e.g. lower capital expenditure).

The storage device described above provides an example of s device wherethe physical hardware and software are designed together such that thesoftware (or control logic) prevents the storage device from enteringstates in which a set of HDDs are active which will cause failure of theoverall device due to insufficient power and/or cooling.

The term ‘computer’ or ‘computing-based device’ is used herein to referto any device with processing capability such that it can executeinstructions. Those skilled in the art will realize that such processingcapabilities are incorporated into many different devices and thereforethe terms ‘computer’ and ‘computing-based device’ each include PCs,servers, mobile telephones (including smart phones), tablet computers,set-top boxes, media players, games consoles, personal digitalassistants and many other devices.

The methods described herein may be performed by software in machinereadable form on a tangible storage medium e.g. in the form of acomputer program comprising computer program code means adapted toperform all the steps of any of the methods described herein when theprogram is run on a computer and where the computer program may beembodied on a computer readable medium. Examples of tangible storagemedia include computer storage devices comprising computer-readablemedia such as disks, thumb drives, memory etc and do not includepropagated signals. Propagated signals may be present in a tangiblestorage media, but propagated signals per se are not examples oftangible storage media. The software can be suitable for execution on aparallel processor or a serial processor such that the method steps maybe carried out in any suitable order, or simultaneously.

This acknowledges that software can be a valuable, separately tradablecommodity. It is intended to encompass software, which runs on orcontrols “dumb” or standard hardware, to carry out the desiredfunctions. It is also intended to encompass software which “describes”or defines the configuration of hardware, such as HDL (hardwaredescription language) software, as is used for designing silicon chips,or for configuring universal programmable chips, to carry out desiredfunctions.

Those skilled in the art will realize that storage devices utilized tostore program instructions can be distributed across a network. Forexample, a remote computer may store an example of the process describedas software. A local or terminal computer may access the remote computerand download a part or all of the software to run the program.Alternatively, the local computer may download pieces of the software asneeded, or execute some software instructions at the local terminal andsome at the remote computer (or computer network). Those skilled in theart will also realize that by utilizing conventional techniques known tothose skilled in the art that all, or a portion of the softwareinstructions may be carried out by a dedicated circuit, such as a DSP,programmable logic array, or the like.

Any range or device value given herein may be extended or alteredwithout losing the effect sought, as will be apparent to the skilledperson.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

It will be understood that the benefits and advantages described abovemay relate to one embodiment or may relate to several embodiments. Theembodiments are not limited to those that solve any or all of the statedproblems or those that have any or all of the stated benefits andadvantages. It will further be understood that reference to ‘an’ itemrefers to one or more of those items.

The steps of the methods described herein may be carried out in anysuitable order, or simultaneously where appropriate. Additionally,individual blocks may be deleted from any of the methods withoutdeparting from the spirit and scope of the subject matter describedherein. Aspects of any of the examples described above may be combinedwith aspects of any of the other examples described to form furtherexamples without losing the effect sought.

The term ‘comprising’ is used herein to mean including the method blocksor elements identified, but that such blocks or elements do not comprisean exclusive list and a method or apparatus may contain additionalblocks or elements.

The term ‘subset’ is used herein to refer to a proper subset, i.e. suchthat a subset is not equal to the set and necessarily excludes at leastone member of the set.

It will be understood that the above description is given by way ofexample only and that various modifications may be made by those skilledin the art. The above specification, examples and data provide acomplete description of the structure and use of exemplary embodiments.Although various embodiments have been described above with a certaindegree of particularity, or with reference to one or more individualembodiments, those skilled in the art could make numerous alterations tothe disclosed embodiments without departing from the spirit or scope ofthis specification.

1. An electronic storage system comprising: a plurality of computer storage media, each of the plurality of computer storage media having an active state and a non active state; a power supply system capable of providing sufficient power for only a subset of the plurality of computer storage media to be in an active state concurrently; a cooling system provisioned to provide sufficient cooling when operating for only a subset of the plurality of computer storage media to be in an active state concurrently; a control mechanism arranged to dynamically control which of the plurality of computer storage media are in an active state; and at least one of: one or more of the plurality of computer storage media having a maximum bandwidth in the active state; at least a portion of the plurality of computer storage media being arranged logically into groups, each group comprising a plurality of computer storage media capable of being in an active state concurrently; or each computer storage media belonging to at least one of a cooling domain and a power domain, a cooling domain comprising one or more computer storage media linked by a cooling constraint and a power domain comprising one or more computer storage media linked by a power constraint;
 2. The electronic storage system according to claim 1, wherein the plurality of computer storage media are located within a device.
 3. The electronic storage system according to claim 1, wherein the control mechanism is arranged to dynamically control which of the plurality of computer storage media are in an active state using the maximum bandwidth of at least one of the one or more the plurality of computer storage media having a maximum bandwidth in the active state.
 4. The electronic storage system according to claim 1, further comprising an interconnect fabric connecting the plurality of computer storage media and a server, the interconnect fabric comprising a plurality of SATA controllers and PCIe switches, wherein each of the plurality of computer storage media is connected to the server via a SATA controller and one or more PCIe switches arranged in a tree structure and wherein the PCIe switches are physically distributed within the electronic storage system.
 5. The electronic storage system according to claim 1, further comprising an interconnect fabric connecting the plurality of devices and a server, the interconnect fabric comprising a plurality of SATA multiplexers arranged in a tree structure.
 6. The electronic storage system according to claim 1, further comprising a server comprising a data store arranged to store a no access' flag associated with each of the plurality of computer storage media and when set, a no access' flag causes all IO requests on a computer storage media to fail.
 7. The electronic storage system according to claim 1, wherein at least one of the plurality of computer storage media includes a spinning disk in an active state.
 8. The electronic storage system according to claim 1, wherein the cooling constraint corresponds to characteristics of the cooling system and the power constraint corresponds to characteristics of the power supply system and wherein each group comprises a plurality of computer storage media in non-overlapping cooling domains and non-overlapping power domains.
 9. The electronic storage system according to claim 8, wherein the plurality of computer storage media are arranged logically into groups such that each group comprises a plurality of computer storage media in non-overlapping cooling domains and non-overlapping power domains and wherein groups are arranged to be either fully colliding or disjoint, wherein two groups are fully colliding if each computer storage media in a first group is a member of the same cooling and power domain as computer storage media in a second group and two groups are disjoint if each computer storage media in a first group is not a member of the same cooling or power domain as any computer storage media in a second group.
 10. The electronic storage system according to claim 1, further comprising a server comprising a scheduler arranged to: receive a burst of data to be written to the electronic storage system divided into portions; add error correction data to each portion; and write each portion to computer storage media from a single group.
 11. The electronic storage system according to claim 1, wherein each portion is divided into a plurality of stripes and each stripe is divided into a plurality of blocks, and wherein adding error correction to each portion comprises: adding one or more blocks comprising redundancy information to each stripe and wherein writing each portion to computer storage media from a single group comprises: for each stripe, writing one block from the stripe to a different one of the computer storage media from the single group.
 12. The electronic storage system according to claim 11, wherein for each stripe, writing one block from the stripe to a different one of the computer storage media from the single group comprises: assembling a sequence of blocks comprising one block from each stripe; and writing each sequence of blocks to a separate computer storage media from the single group.
 13. The electronic storage system according to claim 1, further comprising a server comprising a scheduler arranged to: reorder a plurality of operations into sets of operations operating on the same group of computer storage media, the operations comprising one or more of read, write and delete operations; and schedule sets of operations in an order which maximizes throughput of the electronic storage system.
 14. The electronic storage system according to claim 13, wherein the scheduler is further arranged to receive a burst of operations and to perform reordering on the burst of operations.
 15. The electronic storage system according to claim 13, wherein the scheduler is arranged to perform reordering on a subset of operations in a queue of operations, wherein the subset of operations is defined by a window and wherein the window has a length specified in terms of a number of operations or a period of time.
 16. The electronic storage system according to claim 13, wherein the scheduler is arranged to schedule sets of operations in an order which minimizes switching between groups of computer storage media.
 17. The electronic storage system according to claim 1, further comprising a server comprising a scheduler arranged to: receive a burst of data to be written to the electronic storage system divided into portions; divide each portion into a plurality of segments; add one or more error correction segments; and write each segment to a different computer storage media from a single group.
 18. The electronic storage system according to claim 1, wherein each computer storage media belongs to a cooling domain and a power domain, a cooling domain comprising computer storage media linked by a cooling constraint and a power domain comprising computer storage media linked by a power constraint, the cooling constraint corresponding to characteristics of the cooling system and the power constraint corresponding to characteristics of the power supply system, the electronic storage system further comprising a server comprising a scheduler arranged to: identify a subset of the computer storage media storing data corresponding to a read request; determine a migration path from a current configuration comprising those computer storage media in an active state to a target configuration comprising the identified subset of computer storage media in active state via a plurality of intermediate configurations, wherein each configuration satisfies all power and cooling constraints; and migrating the current configuration of the electronic storage system to the target configuration via the plurality of intermediate configurations.
 19. A method of operating an electronic storage system comprising a plurality of computer storage media and insufficient cooling or power infrastructure for all of the computer storage media to be in an active state concurrently, wherein at least a portion of the plurality of computer storage media are arranged logically into groups, each group comprising a plurality of computer storage media capable of being in the active state concurrently, the method comprising: reordering a plurality of operations into sets of operations operating on the same group of computer storage media; and scheduling sets of operations in an order which maximizes throughput of the electronic storage system.
 20. An electronic storage system comprising: a plurality of computer storage media, each computer storage media having an active state and a non active state, and at least a portion of the plurality of computer storage media being arranged logically into groups, each group comprising a plurality of computer storage media capable of being in an active state concurrently while complying with at least one of a bandwidth constraint, a power constraint, or a cooling constraint; at least a portion of the computer storage media belonging to at least one of a cooling domain or a power domain, a cooling domain comprising computer storage media linked by a cooling constraint and a power domain comprising computer storage media linked by a power constraint; at least one of: a power supply system capable of providing sufficient power for only a subset of the computer storage media to be in an active state concurrently; or a cooling system provisioned to provide sufficient cooling when operating for only a subset of the computer storage media to be in an active state concurrently; and a control mechanism arranged to dynamically control which groups of computer storage media are in an active state according to a request received by the server. 